Entropy Method for Decision Making with Uncertainty

Dear Colleagues,

In today's complex and dynamic world, decision-making processes are frequently challenged by various forms of uncertainty. The need to navigate through this uncertainty while optimizing outcomes has led to the development of advanced computational techniques rooted in fields such as expert systems, distributed learning, rough sets, fuzzy sets, and game theory. Entropy, particularly, holds a crucial position in the realm of information theory and has proven to be efficacious in the context of decision making.

This Special Issue aims to explore the intersection of these fields to advance our understanding of decision making under uncertainty and to propose robust computational solutions.

Theoretical frameworks such as rough sets and fuzzy sets provide formalisms for handling imprecise and uncertain information, allowing decision makers to model ambiguity inherent in real-world scenarios. Additionally, expert systems guide decision-making processes, enhancing the accuracy and reliability of outcomes. Furthermore, distributed learning techniques enable collaborative decision making in decentralized environments, where data may be distributed across multiple sources.

In parallel, game theory, particularly power index analysis, offers insights into strategic interactions among decision makers. By integrating these diverse methodologies, researchers can develop holistic approaches to decision making that account for multiple sources of uncertainty and strategic considerations.

Decision making in Artificial General Intelligence (AGI) and Large Language Models (LLMs) involves complex processes of evaluating information, generating possible courses of action, and selecting the most appropriate one based on predefined goals or criteria. Decision making in both AGI and LLM can be influenced by factors such as uncertainty, incomplete information, and the presence of conflicting objectives. Decision making often involves simulating human-like cognitive processes such as reasoning, planning, and learning.

We invite researchers to submit their original research contributions, case studies, and review articles that address the challenges and opportunities in this multidisciplinary domain.

Prof. Dr. Małgorzata Przybyła-Kasperek
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• rough sets
• fuzzy sets
• expert systems
• distributed learning
• multi-criteria decision making (MCDM)
• game theory
• decision making
• uncertainty
• decision support systems
• information fusion